Abstract
Sensing proteins (receptors) are nanostructures that exhibit very complex behaviors (ions pumping, conformational change, reaction catalysis, etc). They are constituted by a specific sequence of amino acids within a codified spatial organization. The functioning of these macromolecules is intrinsically connected with their spatial structure, which modifications are normally associated with their biological function. With the advance of nanotechnology, the investigation of the electrical properties of receptors has emerged as a demanding issue. Beside the fundamental interest, the possibility to exploit the electrical properties for the development of bioelectronic devices of new generations has attracted major interest. From the experimental side, we investigate three complementary kinds of measurements: (1) current-voltage (I-V) measurements in nanometric layers sandwiched between macroscopic contacts, (2) I-V measurements within an AFM environment in nanometric monolayers deposited on a conducting substrate, and (3) electrochemical impedance spectroscopy measurements on appropriate monolayers of self-assembled samples. From the theoretical side, a microscopic interpretation of these experiments is still a challenging issue. This paper reviews recent theoretical results carried out within the European project, Bioelectronic Olfactory Neuron Device, which provides a first quantitative interpretation of charge transport experiments exploiting static and dynamic electrical properties of several receptors. To this purpose, we have developed an impedance network protein analogue (INPA) which considers the interaction between neighboring amino acids within a given radius as responsible of charge transfer throughout the protein. The conformational change, due to the sensing action produced by the capture of the ligand (photon, odour), induces a modification of the spatial structure and, thus, of the electrical properties of the receptor. By a scaling procedure, the electrical change of the receptor when passing from the native to the active state is used to interpret the macroscopic measurement obtained within different methods. The developed INPA model is found to be very promising for a better understanding of the role of receptor topology in the mechanism responsible of charge transfer. Present results point favorably to the development of a new generation of nano-biosensors within the lab-on-chip strategy.
Highlights
IntroductionSensing proteins (receptors) are nanostructures that exhibit very complex behaviors (ions pumping, conformational change, reaction catalysis, etc)
Sensing proteins are nanostructures that exhibit very complex behaviors
The best known are bacteriorhodopsin, a light sensitive protein whose action is related to a proton pump, and some of the G protein-coupled receptors, a large class of proteins that are sensitive to the light or more generally to the capture of
Summary
Sensing proteins (receptors) are nanostructures that exhibit very complex behaviors (ions pumping, conformational change, reaction catalysis, etc). This paper reviews recent theoretical results carried out within the European project, Bioelectronic Olfactory Neuron Device, which provides a first quantitative interpretation of charge transport experiments exploiting static and dynamic electrical properties of several receptors To this purpose, we have developed an impedance network protein analogue (INPA) which considers the interaction between neighboring amino acids within a given radius as responsible of charge transfer throughout the protein. Recent electrical experiments have been performed on the rat olfactory receptor (OR) OR I7 and on the human OR 17-40 properly deposited on a functionalized gold substrate with the technique of molecular self-assembly These measurements [10,11] showed the possibility to monitor the sensing action of the protein and, in turn, their conformational change by means of the modification of the electrochemical impedance spectrum in the presence of a controlled flux of specific odorants (heptanal, octanal). The model is validated on available experiments and its predictability discussed in the perspective of further experimental confirmations
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